Pandas Profiling Report

Dataset statistics

Number of variables	13
Number of observations	48035
Missing cells	166344
Missing cells (%)	26.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	4.8 MiB
Average record size in memory	104.0 B

Variable types

Numeric	9
DateTime	1
Categorical	2
Unsupported	1

Warnings

`Exit_Reason` has constant value "Abandoned"	Constant
`QueuedTime` is highly correlated with `WaitTime` and 1 other fields	High correlation
`RingTime` is highly correlated with `WaitTime vs QueuedTime`	High correlation
`WaitTime` is highly correlated with `QueuedTime` and 1 other fields	High correlation
`Queue + Ring` is highly correlated with `QueuedTime` and 1 other fields	High correlation
`WaitTime vs QueuedTime` is highly correlated with `RingTime`	High correlation
`channel` is highly correlated with `Exit_Reason`	High correlation
`Exit_Reason` is highly correlated with `channel`	High correlation
`Party_Name` has 48035 (100.0%) missing values	Missing
`TalkTime` has 35313 (73.5%) missing values	Missing
`HoldTime` has 35426 (73.8%) missing values	Missing
`WrapTime` has 47570 (99.0%) missing values	Missing
`QueuedTime` is highly skewed (γ1 = 28.7180407)	Skewed
`TalkTime` is highly skewed (γ1 = 37.77623424)	Skewed
`HoldTime` is highly skewed (γ1 = 66.00560691)	Skewed
`WaitTime` is highly skewed (γ1 = 28.86204012)	Skewed
`Queue + Ring` is highly skewed (γ1 = 28.86204012)	Skewed
`df_index` has unique values	Unique
`Party_Name` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`QueuedTime` has 2023 (4.2%) zeros	Zeros
`RingTime` has 37344 (77.7%) zeros	Zeros
`TalkTime` has 12596 (26.2%) zeros	Zeros
`HoldTime` has 12519 (26.1%) zeros	Zeros
`WaitTime` has 564 (1.2%) zeros	Zeros
`Queue + Ring` has 564 (1.2%) zeros	Zeros
`WaitTime vs QueuedTime` has 37344 (77.7%) zeros	Zeros

Reproduction

Analysis started	2021-02-26 15:35:05.545510
Analysis finished	2021-02-26 15:35:17.293859
Duration	11.75 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

df_index
Real number (ℝ_≥0)

UNIQUE

Distinct	48035
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	248385.8969
Minimum	0
Maximum	613885
Zeros	1
Zeros (%)	< 0.1%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	32684.7
Q1	125577.5
median	185058
Q3	392455.5
95-th percentile	564082.9
Maximum	613885
Range	613885
Interquartile range (IQR)	266878

Descriptive statistics

Standard deviation	168480.0231
Coefficient of variation (CV)	0.6782994736
Kurtosis	-0.8728868399
Mean	248385.8969
Median Absolute Deviation (MAD)	102614
Skewness	0.6137574687
Sum	1.193121656 × 10¹⁰
Variance	2.838551819 × 10¹⁰
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
359355	1	< 0.1%
137718	1	< 0.1%
374171	1	< 0.1%
158200	1	< 0.1%
227834	1	< 0.1%
612726	1	< 0.1%
410109	1	< 0.1%
169184	1	< 0.1%
152063	1	< 0.1%
Other values (48025)	48025	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%

Value	Count	Frequency (%)
613885	1	< 0.1%
613840	1	< 0.1%
613839	1	< 0.1%
613822	1	< 0.1%
613808	1	< 0.1%

Call_Start
Date

Distinct	47720
Distinct (%)	99.3%
Missing	0
Missing (%)	0.0%
Memory size	375.4 KiB

Minimum	2020-01-01 08:22:41.999998
Maximum	2021-02-21 12:20:36.000004

Histogram

Histogram with fixed size bins (bins=50)

Exit_Reason
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	375.4 KiB

Abandoned	48035

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Characters and Unicode

Total characters	432315
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Abandoned
2nd row	Abandoned
3rd row	Abandoned
4th row	Abandoned
5th row	Abandoned

Value	Count	Frequency (%)
Abandoned	48035	100.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
abandoned	48035	100.0%

Most occurring characters

Value	Count	Frequency (%)
n	96070	22.2%
d	96070	22.2%
A	48035	11.1%
b	48035	11.1%
a	48035	11.1%
o	48035	11.1%
e	48035	11.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	384280	88.9%
Uppercase Letter	48035	11.1%

Most frequent character per category

Value	Count	Frequency (%)
n	96070	25.0%
d	96070	25.0%
b	48035	12.5%
a	48035	12.5%
o	48035	12.5%
e	48035	12.5%

Value	Count	Frequency (%)
A	48035	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	432315	100.0%

Most frequent character per script

Value	Count	Frequency (%)
n	96070	22.2%
d	96070	22.2%
A	48035	11.1%
b	48035	11.1%
a	48035	11.1%
o	48035	11.1%
e	48035	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	432315	100.0%

Most frequent character per block

Value	Count	Frequency (%)
n	96070	22.2%
d	96070	22.2%
A	48035	11.1%
b	48035	11.1%
a	48035	11.1%
o	48035	11.1%
e	48035	11.1%

Party_Name
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	48035
Missing (%)	100.0%
Memory size	375.4 KiB

channel
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	375.4 KiB

SEO	39438
PPC	8597

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	144105
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	SEO
2nd row	SEO
3rd row	SEO
4th row	SEO
5th row	SEO

Value	Count	Frequency (%)
SEO	39438	82.1%
PPC	8597	17.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
seo	39438	82.1%
ppc	8597	17.9%

Most occurring characters

Value	Count	Frequency (%)
S	39438	27.4%
E	39438	27.4%
O	39438	27.4%
P	17194	11.9%
C	8597	6.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	144105	100.0%

Most frequent character per category

Value	Count	Frequency (%)
S	39438	27.4%
E	39438	27.4%
O	39438	27.4%
P	17194	11.9%
C	8597	6.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	144105	100.0%

Most frequent character per script

Value	Count	Frequency (%)
S	39438	27.4%
E	39438	27.4%
O	39438	27.4%
P	17194	11.9%
C	8597	6.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	144105	100.0%

Most frequent character per block

Value	Count	Frequency (%)
S	39438	27.4%
E	39438	27.4%
O	39438	27.4%
P	17194	11.9%
C	8597	6.0%

QueuedTime
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	922
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	73.81804934
Minimum	0
Maximum	14829
Zeros	2023
Zeros (%)	4.2%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	5
median	26
Q3	83
95-th percentile	276
Maximum	14829
Range	14829
Interquartile range (IQR)	78

Descriptive statistics

Standard deviation	206.6660565
Coefficient of variation (CV)	2.799668352
Kurtosis	1545.004505
Mean	73.81804934
Median Absolute Deviation (MAD)	23
Skewness	28.7180407
Sum	3545850
Variance	42710.85893
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4	3557	7.4%
3	2761	5.7%
0	2023	4.2%
2	1870	3.9%
1	1687	3.5%
5	1580	3.3%
7	932	1.9%
6	902	1.9%
8	858	1.8%
9	688	1.4%
Other values (912)	31177	64.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2023	4.2%
1	1687	3.5%
2	1870	3.9%
3	2761	5.7%
4	3557	7.4%

Value	Count	Frequency (%)
14829	1	< 0.1%
14689	1	< 0.1%
12458	1	< 0.1%
8718	1	< 0.1%
6296	1	< 0.1%

RingTime
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	30
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.429187051
Minimum	0
Maximum	48
Zeros	37344
Zeros (%)	77.7%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	10
Maximum	48
Range	48
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	3.817586402
Coefficient of variation (CV)	2.671159383
Kurtosis	12.89926706
Mean	1.429187051
Median Absolute Deviation (MAD)	0
Skewness	3.480064307
Sum	68651
Variance	14.57396594
Monotocity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
0	37344	77.7%
1	1683	3.5%
2	1508	3.1%
3	1346	2.8%
4	1079	2.2%
5	766	1.6%
6	604	1.3%
7	473	1.0%
20	436	0.9%
8	413	0.9%
Other values (20)	2383	5.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	37344	77.7%
1	1683	3.5%
2	1508	3.1%
3	1346	2.8%
4	1079	2.2%

Value	Count	Frequency (%)
48	1	< 0.1%
43	1	< 0.1%
34	1	< 0.1%
27	1	< 0.1%
26	1	< 0.1%

TalkTime
Real number (ℝ_≥0)

MISSING
SKEWED
ZEROS

Distinct	69
Distinct (%)	0.5%
Missing	35313
Missing (%)	73.5%
Infinite	0
Infinite (%)	0.0%

Mean	0.5918094639
Minimum	0
Maximum	677
Zeros	12596
Zeros (%)	26.2%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	677
Range	677
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	10.28238686
Coefficient of variation (CV)	17.37448872
Kurtosis	1949.968285
Mean	0.5918094639
Median Absolute Deviation (MAD)	0
Skewness	37.77623424
Sum	7529
Variance	105.7274795
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	12596	26.2%
32	6	< 0.1%
18	6	< 0.1%
19	6	< 0.1%
20	5	< 0.1%
24	4	< 0.1%
29	4	< 0.1%
27	4	< 0.1%
26	4	< 0.1%
34	3	< 0.1%
Other values (59)	84	0.2%
(Missing)	35313	73.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12596	26.2%
1	3	< 0.1%
6	1	< 0.1%
8	1	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
677	1	< 0.1%
431	1	< 0.1%
364	1	< 0.1%
292	1	< 0.1%
219	1	< 0.1%

HoldTime
Real number (ℝ_≥0)

MISSING
SKEWED
ZEROS

Distinct	20
Distinct (%)	0.2%
Missing	35426
Missing (%)	73.8%
Infinite	0
Infinite (%)	0.0%

Mean	0.06733285748
Minimum	0
Maximum	215
Zeros	12519
Zeros (%)	26.1%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	215
Range	215
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.444495435
Coefficient of variation (CV)	36.30464422
Kurtosis	5158.649742
Mean	0.06733285748
Median Absolute Deviation (MAD)	0
Skewness	66.00560691
Sum	849
Variance	5.975557932
Monotocity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
0	12519	26.1%
1	42	0.1%
2	14	< 0.1%
4	6	< 0.1%
3	5	< 0.1%
10	3	< 0.1%
6	3	< 0.1%
5	2	< 0.1%
9	2	< 0.1%
11	2	< 0.1%
Other values (10)	11	< 0.1%
(Missing)	35426	73.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12519	26.1%
1	42	0.1%
2	14	< 0.1%
3	5	< 0.1%
4	6	< 0.1%

Value	Count	Frequency (%)
215	1	< 0.1%
94	1	< 0.1%
91	1	< 0.1%
77	1	< 0.1%
48	1	< 0.1%

WrapTime
Real number (ℝ_≥0)

MISSING

Distinct	150
Distinct (%)	32.3%
Missing	47570
Missing (%)	99.0%
Infinite	0
Infinite (%)	0.0%

Mean	64.57204301
Minimum	0
Maximum	981
Zeros	72
Zeros (%)	0.1%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	5
median	12
Q3	60
95-th percentile	321.8
Maximum	981
Range	981
Interquartile range (IQR)	55

Descriptive statistics

Standard deviation	123.676945
Coefficient of variation (CV)	1.915332692
Kurtosis	12.68983522
Mean	64.57204301
Median Absolute Deviation (MAD)	10
Skewness	3.158296191
Sum	30026
Variance	15295.98672
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	72	0.1%
10	25	0.1%
12	21	< 0.1%
7	18	< 0.1%
8	18	< 0.1%
5	15	< 0.1%
4	14	< 0.1%
11	14	< 0.1%
3	14	< 0.1%
14	14	< 0.1%
Other values (140)	240	0.5%
(Missing)	47570	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	72	0.1%
1	1	< 0.1%
2	10	< 0.1%
3	14	< 0.1%
4	14	< 0.1%

Value	Count	Frequency (%)
981	1	< 0.1%
792	1	< 0.1%
666	1	< 0.1%
617	1	< 0.1%
586	1	< 0.1%

WaitTime
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	922
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	75.24723639
Minimum	0
Maximum	14829
Zeros	564
Zeros (%)	1.2%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	8
median	27
Q3	83
95-th percentile	276.3
Maximum	14829
Range	14829
Interquartile range (IQR)	75

Descriptive statistics

Standard deviation	206.2781788
Coefficient of variation (CV)	2.741338934
Kurtosis	1555.881676
Mean	75.24723639
Median Absolute Deviation (MAD)	22
Skewness	28.86204012
Sum	3614501
Variance	42550.68705
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5	2030	4.2%
4	1934	4.0%
6	1625	3.4%
7	1579	3.3%
3	1572	3.3%
8	1505	3.1%
9	1150	2.4%
2	1020	2.1%
10	1012	2.1%
11	918	1.9%
Other values (912)	33690	70.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	564	1.2%
1	726	1.5%
2	1020	2.1%
3	1572	3.3%
4	1934	4.0%

Value	Count	Frequency (%)
14829	1	< 0.1%
14689	1	< 0.1%
12458	1	< 0.1%
8718	1	< 0.1%
6296	1	< 0.1%

Queue + Ring
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	922
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	75.24723639
Minimum	0
Maximum	14829
Zeros	564
Zeros (%)	1.2%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	8
median	27
Q3	83
95-th percentile	276.3
Maximum	14829
Range	14829
Interquartile range (IQR)	75

Descriptive statistics

Standard deviation	206.2781788
Coefficient of variation (CV)	2.741338934
Kurtosis	1555.881676
Mean	75.24723639
Median Absolute Deviation (MAD)	22
Skewness	28.86204012
Sum	3614501
Variance	42550.68705
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5	2030	4.2%
4	1934	4.0%
6	1625	3.4%
7	1579	3.3%
3	1572	3.3%
8	1505	3.1%
9	1150	2.4%
2	1020	2.1%
10	1012	2.1%
11	918	1.9%
Other values (912)	33690	70.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	564	1.2%
1	726	1.5%
2	1020	2.1%
3	1572	3.3%
4	1934	4.0%

Value	Count	Frequency (%)
14829	1	< 0.1%
14689	1	< 0.1%
12458	1	< 0.1%
8718	1	< 0.1%
6296	1	< 0.1%

WaitTime vs QueuedTime
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	30
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.429187051
Minimum	0
Maximum	48
Zeros	37344
Zeros (%)	77.7%
Memory size	375.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	10
Maximum	48
Range	48
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	3.817586402
Coefficient of variation (CV)	2.671159383
Kurtosis	12.89926706
Mean	1.429187051
Median Absolute Deviation (MAD)	0
Skewness	3.480064307
Sum	68651
Variance	14.57396594
Monotocity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
0	37344	77.7%
1	1683	3.5%
2	1508	3.1%
3	1346	2.8%
4	1079	2.2%
5	766	1.6%
6	604	1.3%
7	473	1.0%
20	436	0.9%
8	413	0.9%
Other values (20)	2383	5.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	37344	77.7%
1	1683	3.5%
2	1508	3.1%
3	1346	2.8%
4	1079	2.2%

Value	Count	Frequency (%)
48	1	< 0.1%
43	1	< 0.1%
34	1	< 0.1%
27	1	< 0.1%
26	1	< 0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	Call_Start	Exit_Reason	Party_Name	channel	QueuedTime	TalkTime	HoldTime	WrapTime	WaitTime	Queue + Ring
0	0	2020-01-01 08:22:41.999998	Abandoned	NaN	SEO	11	NaN	NaN	NaN	11	11
1	1	2020-01-01 08:54:11.999998	Abandoned	NaN	SEO	115	NaN	NaN	NaN	115	115
2	2	2020-01-01 10:41:51.999997	Abandoned	NaN	SEO	25	NaN	NaN	NaN	25	25
3	3	2020-01-01 10:47:42.999996	Abandoned	NaN	SEO	60	NaN	NaN	NaN	60	60
4	4	2020-01-01 11:06:46.000000	Abandoned	NaN	SEO	20	NaN	NaN	NaN	20	20
5	5	2020-01-01 11:25:49.000002	Abandoned	NaN	SEO	7	NaN	NaN	NaN	7	7
6	6	2020-01-01 15:08:38.000002	Abandoned	NaN	SEO	23	NaN	NaN	NaN	23	23
7	7	2020-01-01 16:38:39.000005	Abandoned	NaN	SEO	119	NaN	NaN	NaN	119	119
8	8	2020-01-01 16:53:30.999999	Abandoned	NaN	SEO	12	NaN	NaN	NaN	12	12
9	9	2020-01-01 16:58:58.999999	Abandoned	NaN	SEO	20	NaN	NaN	NaN	20	20

Last rows

	df_index	Call_Start	Exit_Reason	Party_Name	channel	QueuedTime	TalkTime	HoldTime	WrapTime	WaitTime	Queue + Ring
48025	613737	2021-02-20 15:55:19.000004	Abandoned	NaN	SEO	45	NaN	NaN	NaN	45	45
48026	613746	2021-02-20 15:59:57.999999	Abandoned	NaN	SEO	7	NaN	NaN	NaN	7	7
48027	613754	2021-02-20 16:11:08.000004	Abandoned	NaN	SEO	7	NaN	NaN	NaN	7	7
48028	613764	2021-02-20 16:21:58.000000	Abandoned	NaN	SEO	4	NaN	NaN	NaN	4	4
48029	613774	2021-02-20 16:29:51.999999	Abandoned	NaN	SEO	7	NaN	NaN	NaN	7	7
48030	613808	2021-02-21 09:28:53.999996	Abandoned	NaN	SEO	60	NaN	NaN	NaN	60	60
48031	613822	2021-02-21 10:16:28.000004	Abandoned	NaN	SEO	15	NaN	NaN	NaN	15	15
48032	613839	2021-02-21 10:50:54.000001	Abandoned	NaN	SEO	166	NaN	NaN	NaN	166	166
48033	613840	2021-02-21 10:51:53.000003	Abandoned	NaN	SEO	165	NaN	NaN	NaN	165	165
48034	613885	2021-02-21 12:20:36.000004	Abandoned	NaN	SEO	8	NaN	NaN	NaN	8	8

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows